How to Become an AI Security Engineer

Only about 14% of organizations believe they currently have the talent to secure their AI systems. That's not an outside estimate - it's what the organizations deploying AI systems say about themselves, according to the World Economic Forum's 2025 Global AI Jobs research.How to Become an AI Security Engineer is the complete field guide to filling that gap: the engineer who thinks like an attacker, understands how large language models and AI agents actually behave, and builds the red-teaming, defenses, and monitoring that keep real AI systems from being manipulated in production.Across 13 chapters, you'll get: - A clear breakdown of what this role actually does - and a dedicated chapter untangling six overlapping titles (AI Red Teamer, LLM Security Engineer, ML Security Engineer, AI Trust & Safety Analyst, LLM Security Architect, AI Safety Engineer) so you stop applying under the wrong one- Two Roads In - a dedicated chapter for both entry paths: security professionals moving into AI, and AI/software engineers moving into security- The real attack surface: prompt injection (direct and indirect), jailbreaking, data poisoning, model extraction, and agent security - permissions, tool misuse, and containment- Hands-on grounding in the field's real, named frameworks and tools: the OWASP Top 10 for LLM Applications, MITRE ATLAS, and open-source red-teaming tools Garak and PyRIT- A complete 180-day learning roadmap, sequenced month by month- Ten hands-on portfolio projects - each with a specific objective, techniques and tools used, documented findings, a proposed defense, and honest lessons learned- Real code references for automated adversarial scanning and defense-in-depth guardrail pipelines- A grounded, honestly-caveated breakdown of compensation, a documented career…